Data Manager – SME & Merchant Analytics at Palmpay Limited

PalmPay is an Africa-focused fintech firm, launched in 2019. PalmPay is a mobile payments platform that offers a number of financial services.

We are recruiting to fill the position below:

Job Title: Data Manager – SME & Merchant Analytics

Location: Lagos

Role Overview

• We are hiring a Data Manager to lead analytics and performance intelligence across a large-scale SME and merchant ecosystem.
• This role is responsible for how data is structured, interpreted, and used to drive decisions across merchant growth, operational execution, and portfolio performance.
• The ideal candidate is comfortable working with high-volume transactional data, operational activity data, and outcome metrics—and can translate these into insights that shape strategy, execution, and accountability.
• This role works closely with business, product, risk, and operations teams and is expected to operate close to real decision-making, not just reporting.

Key Responsibilities
Data Ownership & Governance:

• Own the end-to-end data lifecycle across merchant activity, transactions, operational execution, and portfolio outcomes.
• Define and maintain clear, consistent metrics used across dashboards, reports, and performance reviews.
• Ensure data quality, accuracy, and traceability across multiple data sources and systems.
• Document definitions, assumptions, and logic behind key metrics to avoid ambiguity.

Merchant & Transaction Analytics:

• Analyse transaction patterns to understand merchant behaviour, income stability, growth trajectories, and volatility.
• Develop merchant segmentation frameworks using behavioural and performance signals.
• Track merchant onboarding, activation, retention, and inactivity, identifying drivers of drop-off and reactivation.
• Surface early indicators of performance shifts using transaction and activity data.

Performance & Execution Analytics:

• Build performance tracking frameworks for operational and field teams involved in merchant acquisition, activation, verification, and follow-up.
• Monitor productivity, conversion rates, turnaround times, and quality metrics across teams and locations.
• Identify execution bottlenecks and efficiency gaps and provide evidence-based recommendations.
• Support managers with clear, actionable performance dashboards.

Credit & Portfolio Performance Analytics:

• Monitor how merchants progress through approval, utilisation, and repayment stages.
• Analyse approval funnels, utilisation behaviour, and portfolio trends across segments and geographies.
• Track performance migration and early stress signals within the portfolio.
• Support evidence-based calibration of thresholds, limits, and operating rules.

Dashboards, Reporting & Decision Support:

• Design and maintain dashboards used in daily operations, weekly performance reviews, and leadership meetings.
• Translate complex datasets into concise insights, trade-offs, and recommendations.
• Provide regular performance summaries that explain what changed, why it changed, and what to do next.
• Support planning, forecasting, and performance reviews with reliable data.

Cross-Functional Collaboration:

• Work closely with Product, Engineering, Risk, Operations, Finance, and Compliance teams to align data with business needs.
• Support internal governance, audits, and external reporting requirements where relevant.
• Act as a thought partner to stakeholders, helping teams ask better questions of the data.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Economics, Computer Science, Engineering, or a related field.
• 4–7 years of experience in data analytics, business intelligence, or data management roles.
• Strong SQL skills and experience working directly with large, real-world datasets.
• Proven experience building dashboards using tools such as Power BI, Tableau, Looker, or similar.
• Strong ability to communicate insights clearly to non-technical stakeholders.
• Experience working with merchant, SME, payments, or lending data.
• Exposure to field-based or distributed operational models.
• Python, R, or similar tools for advanced analysis or automation.
• Experience in fast-growing or operationally complex environments.

What Success Looks Like

• Business and leadership teams trust and rely on the data to make decisions.
• Performance issues are identified early and addressed proactively.
• Merchant and portfolio behaviour is well understood and measurable.
• Dashboards and reports are actively used, not ignored.
• Decisions improve because the underlying system is visible and grounded in data.

Application Closing Date
Not Specified

How to Apply
Interested and qualified candidates should:
Click here to apply online